Lab 1

Read in the data

sf_trees <- read.csv(here("data", "sf_trees", "sf_trees.csv"))

plot the top 5 legal status

top_5_status <- sf_trees %>% 
  group_by(legal_status) %>%  
  summarize(tree_count = n()) %>% 
  slice_max(tree_count, n = 5) %>%
  arrange(-tree_count)
  
tree_plot <- ggplot(data = top_5_status, aes(x = fct_reorder(legal_status, tree_count), 
                                y = tree_count)) + 
  geom_col() +
  labs(y = 'Tree count', x = 'Legal Status') +
  coord_flip() +
  theme_minimal()

tree_plot

Keep obs where legal status is “Permitted Site” and caretaker is “MTA”

permitted_mia <- sf_trees %>% 
  filter(legal_status == "Permitted Site" & caretaker == "MTA")

Keep Blackwood acacia trees, keep only legal_status, date, latitude, longitude columns

blackwood_acacia <- sf_trees %>% 
  filter(str_detect(species, "Blackwood Acacia")) %>% 
  select(legal_status, date, latitude, longitude)

#str_detect for if the name like this is next to another scientific name
### now make a plot

ggplot(data = blackwood_acacia, aes(x = longitude, y = latitude)) + geom_point()

use tidyr:: separate() to separate one column into multiple (in this case, separate common and scientific name) and use tidyr :: unite() to bring them back together

sf_tress_sep <- sf_trees %>% separate(species, into = c('spp_scientific', 'spp_common'), sep = " :: ")

sf_trees_unite <- sf_trees %>% 
  unite("id_status", tree_id:species, sep = '_NEW_')

Make some actual maps!

blackwood_acacia_sf <- blackwood_acacia %>% 
  drop_na(longitude, latitude) %>% 
  st_as_sf(coords = c('longitude', 'latitude'))

# now you have coordinates as points and can plot them using simple features tool

st_crs(blackwood_acacia_sf) <- 4326 #basically a coordinate reference system, basic latitude and longitude

ggplot(data = blackwood_acacia_sf) + geom_sf(color = 'darkgreen') + theme_minimal()

### Read in SF streets data (sf in this case at the end stands for simple features)

sf_map_sf <- read_sf(here('data', 'sf_map', 'tl_2017_06075_roads.shp')) %>% 
  st_transform(4326) 

# st_crs(sf_map_sf) see what coordinate system you are working with and itf you have to change it

ggplot() + 
  geom_sf(data = sf_map_sf, size = 0.1, color = 'darkgrey') +
  geom_sf(data = blackwood_acacia_sf, color = 'darkgreen', size = 0.5) + theme_void() +
  labs(title = 'Blackwood acacias in San Francisco')

Interactive Map

tmap_mode('view')

## tmap mode set to interactive viewing

tm_shape(blackwood_acacia_sf) + tm_dots()